898), eGFR reduction (aHR=3.484), and CKD progression (aHR=1.984)(all P less then 0.01). In conclusion, patients with HBV-related HCC treated with TDFand frequent CT evaluationsshould be closely monitored for thedetection of associated renal dysfunction. This article is protected by copyright. All rights reserved.Autism spectrum disorder (ASD)-like phenotypes in murine models are linked to elevated proinflammatory cytokine profiles caused by maternal immune activation (MIA) but whether MIA alters the immune response in the offspring remains unclear. Polyinosinicpolycytidylic acid (poly[IC]) was used to induce MIA in immunocompetent and control TLR3-deficient pregnant mice and cytokine levels were measured in maternal and fetal organs. Furthermore, cytokines and behaviour responses were tested after challenge with lipopolysaccharide in 7-day-old and adult mice. MIA induced on E12 resulted in changes in the cytokine expression profile in maternal and fetal organs and correlated with TNFα and IL-18 dysregulation in immune organs and brains from neonatal mice born to MIA-induced dams. Such changes further correlated with altered behavioural responses in adulthood. MIA induced by pathogens during pregnancy can interfere with the development of the fetal immune and nervous systems leading to dysfunctional immune responses and behaviour in offspring. This article is protected by copyright. All rights reserved.Responding to social distancing guidelines, small-group teachers in the University of British Columbia's Undergraduate Medical Program were required to transition from face-to-face small-group teaching to a synchronous, online format within days. https://www.selleckchem.com/products/fdi-6.html To do this effectively, teachers needed to simultaneously master new technological skills, respond to altered group dynamics and ensure that learning objectives were met. In the context of a Distributed Medical Education program, this was a daunting task, with approximately 125 faculty teaching 576 learners across small-group contexts at four sites making the transition simultaneously. This article is protected by copyright. All rights reserved.Atopic dermatitis (AD) is a common inflammatory skin disease with high prevalence both in children (15-30%) and adults (2-10%); limited data are available for the elderly. Elderly patients are challenging showing frequent multiple comorbidities, associated polypharmacy, and common previously treatments failure. We performed a retrospective observational study on elderly (? 65 year-old) patients treated with dupilumab, monoclonal antibody to the shared alpha subunit of the IL4 and IL-13 receptor approved for the treatment of moderate-to-severe AD in adults. This article is protected by copyright. All rights reserved.Multiple Mini-Interviews (MMIs) are one of the most effective and popular interview methods for medical school candidate selection. A standardized set of scenarios/questions and responses are pre-determined and candidates rotate through various stations to meet examiners in face-to-face, in-person, mini-interviews during a finite time allotment. The objective of MMIs are to generally to assess candidates' characteristics in different domains such as ethics and morality, communication skills, and critical thinking. MMIs can be reliable and feasible, moreso than traditional interview methods. This article is protected by copyright. All rights reserved.The UK National Diabetes Inpatient COVID Response Group was formed at the end of March 2020 to support the provision of diabetes inpatient care during the COVID pandemic. It was formed in response to two emerging needs. First to ensure that basic diabetes services are secured and maintained at a time when there was a call for re-deployment to support the need for general medical expertise across secondary care services. The second was to provide simple safe diabetes guidelines for use by specialists and non-specialists treating inpatients with or suspected of COVID-19 infection. To date the group, comprising UK-based specialists in diabetes, pharmacy and psychology, have produced two sets of guidelines which will be continually revised as new evidence emerges. It is supported by Diabetes UK, the Association of British Clinical Diabetologists and NHS England. © 2020 Diabetes UK.Individualized treatment rules (ITRs) tailor medical treatments according to patient-specific characteristics in order to optimize patient outcomes. Data from randomized controlled trials (RCTs) are used to infer valid ITRs using statistical and machine learning methods. However, RCTs are usually conducted under specific inclusion/exclusion criteria, thus limiting their generalizability to a broader patient population in real-world practice settings. Because electronic health records (EHRs) document treatment prescriptions in the real world, transferring information in EHRs to RCTs, if done appropriately, could potentially improve the performance of ITRs, in terms of precision and generalizability. In this work, we propose a new domain adaptation method to learn ITRs by incorporating information from EHRs. Unless we assume that there is no unmeasured confounding in EHRs, we cannot directly learn the optimal ITR from the combined EHR and RCT data. Instead, we first pretrain "super" features from EHRs that summarize physician treatment decisions and patient observed benefits in the real world, as these are likely to be informative of the optimal ITRs. We then augment the feature space of the RCT and learn the optimal ITRs by stratifying by super features using subjects enrolled in RCT. We adopt Q-learning and a modified matched-learning algorithm for estimation. We present heuristic justification of our method and conduct simulation studies to demonstrate the performance of super features. Finally, we apply our method to transfer information learned from EHRs of patients with type 2 diabetes to learn individualized insulin therapies from RCT&nbsp;data. © 2020 The International Biometric Society.We consider Bayesian logistic regression models with group-structured covariates. In high-dimensional settings, it is often assumed that only a small portion of groups are significant, and thus, consistent group selection is of significant importance. While consistent frequentist group selection methods have been proposed, theoretical properties of Bayesian group selection methods for logistic regression models have not been investigated yet. In this paper, we consider a hierarchical group spike and slab prior for logistic regression models in high-dimensional settings. Under mild conditions, we establish strong group selection consistency of the induced posterior, which is the first theoretical result in the Bayesian literature. Through simulation studies, we demonstrate that the proposed method outperforms existing state-of-the-art methods in various settings. We further apply our method to a magnetic resonance imaging data set for predicting Parkinson's disease and show its benefits over other&nbsp;contenders. © 2020 The International Biometric Society.